A Review of Concordance and Quality in Clinical Guidelines for Hormonal Contraceptives to Mitigate Drug-Drug Interactions in Women With Epilepsy.

PURPOSE: Concomitant use of hormonal contraceptive agents (HCAs) and enzyme-inducting antiepileptic drugs (EIAEDs) may lead to contraceptive failure and unintended pregnancy. This review identified and evaluated concordance and quality of clinical treatment guidelines related to the use of HCAs in women with epilepsy (WWE) receiving EIAEDs. METHODS: Relevant clinical guidelines were identified across four databases and were independently evaluated for quality utilizing the AGREE-II protocol instrument. Quality in this context is defined as the rigor and transparency of the methodologies used to develop the guideline. Guidelines were further assessed in terms of concordance and discordance with the latest body of knowledge concerning the use of hormonal contraception in the presence of EIAEDs. RESULTS: A total of n = 5 guidelines were retrieved and evaluated. Overall guideline scores ranged from 17% to 92%, while individual domain scores ranged from 0% to 100%. Contraceptive guidelines consistently recommended the use of intrauterine systems and long-acting injectables in the presence of EIAEDs, recommended against the use of oral, transdermal, and vaginal ring contraceptives, and differed regarding recommendations related to implants. Guidelines agreed regarding recommendations that women treated with EIAEDs should receive intrauterine systems and long-acting injectables; however, the suggested frequency of administration of injectable contraceptives differed. The use of intrauterine systems in this population is supported by evidence, but there is uncertainty surrounding the use of long-acting injectables and contraceptive implants. CONCLUSIONS: To mitigate the risk of unintended pregnancy and its consequences, recommendations related to implants and long-acting injectable contraceptives should be evidence-based.

Proton pump inhibitors decrease efficacy of palbociclib in patients with metastatic breast.

OBJECTIVES: The objective of this investigation was to assess the impact of concurrent proton pump inhibitors (PPIs) on progression-free survival (PFS) in patients with hormone receptor-positive and HER2-negative metastatic breast cancer (mBC) who received palbociclib as first-line or successives therapy. MATERIALS AND METHODS: A retrospective observational study was conducted, enrolling patients diagnosed with estrogen receptor-positive, human epidermal growth factor receptor 2-negative mBC, and eligible for palbociclib treatment. Patients were categorized as "concurrent PPIs" if they received PPIs for at least two-thirds of the palbociclib therapy duration, and as "no concurrent PPIs" if they did not receive PPIs during the course of palbociclib treatment. RESULTS: A total of 165 patients were included in the study. Among first-line patients treated with palbociclib, those using concurrent PPIs exhibited a PFS of 8.88 months, while patients using palbociclib without concurrent PPIs had a PFS of 67.81 months (p < 0.0001). In second-line or subsequent treatments, patients on palbociclib with concurrent PPIs had a PFS of 7.46 months, whereas those using palbociclib without concurrent PPIs had a PFS of 17.29 months (p = 0.122). CONCLUSION: This study demonstrates that the concurrent use of PPIs in mBC patients receiving palbociclib negatively affects PFS, particularly in the first-line setting. Nevertheless, further investigation is warranted to explore the impact of PPIs on cycle-dependent kinase 4/6 inhibitors.

Effects of Food, Gastric Acid Reduction, and Strong CYP3A Induction on the Pharmacokinetics of Tasurgratinib, a Novel Selective Fibroblast Growth Factor Receptor Inhibitor.

We conducted this three-part study in healthy subjects to investigate the pharmacokinetics of tasurgratinib (orally available selective inhibitor of fibroblast growth factor receptor 1-3) and M2 (its major metabolite) under different conditions. In Part A, subjects received tasurgratinib 35 mg either fed with a high-fat meal or fasted. In Parts B and C, subjects received tasurgratinib 35 mg alone or with either rabeprazole (acid-reducing agent) 20 mg (Part B) or rifampin (strong CYP3A inducer) 600 mg (Part C). Primary endpoints were maximum concentration (Cmax), and areas under the plasma concentration-time curve to time of last quantifiable concentration (AUC(0-t)) and extrapolated to infinite time (AUC(0-inf)). Forty-two subjects were enrolled, 14 each into Parts A, B, and C. In Part A, administration of tasurgratinib with a high-fat meal resulted in 33% reduction in Cmax and ∼23% reduction in AUC(0-t) and AUC(0-inf) of tasurgratinib, and 47% reduction in Cmax with ∼30% reduction in AUC(0-t) and AUC(0-inf) of M2. In Part B, co-administration of rabeprazole at steady state resulted in no/weak interaction with tasurgratinib (∼8% increase in AUC(0-t) and AUC(0-inf) without an effect on Cmax) and M2 (∼18% increase in AUC(0-t) and AUC(0-inf) without an effect on Cmax). In Part C, co-administration of rifampin at steady state resulted in a weak interaction with tasurgratinib (∼16% reduction in AUC(0-t) and AUC(0-inf)) and M2 (∼12% reduction in AUC(0-t) and AUC(0-inf)). Administration of tasurgratinib with a high-fat meal appeared to reduce systemic exposure of tasurgratinib, however co-administration with an acid-reducing agent or a CYP3A inducer had a minimal impact on pharmacokinetics.

Carboxylesterase 1-Based Drug-Drug Interaction Potential of Remimazolam: In-Vitro Studies and Literature Review.

BACKGROUND: The ultra-short-acting benzodiazepine remimazolam, approved for procedural sedation and general anesthesia, is inactivated by carboxylesterase 1 (CES1). OBJECTIVE: Remimazolam´s involvement in CES1-mediated drug-drug interactions (DDIs) was investigated. METHODS: Possible interactions of remimazolam were studied in co-exposure experiments with eleven different drugs. Further, substrates and inhibitors of CES1, identified in the literature, were evaluated for possible in-vivo inhibition using pharmacokinetic and Ki or IC50 values. Compounds with only one published inhibitory concentration and CES1 substrates lacking inhibition data were assigned conservative Ki values. RESULTS: In human liver homogenates and/or blood cells, remimazolam showed no significant inhibition of esmolol and landiolol metabolism, which, in turn, at up to 98 and 169 µM, respectively, did not inhibit remimazolam hydrolysis by human liver homogenates. In human liver S9 fractions, IC50 values ranged from 0.69 µM (simvastatin) and 57 µM (diltiazem) to > 100 µM (atorvastatin) and, for the remaining test items (bupropion, carvedilol, nelfinavir, nitrendipine, and telmisartan), they ranged from 126 to 658 µM. Remifentanil was ineffective even at 1250 µM. Guidance-conforming evaluation revealed no relevant drug-drug interactions with remimazolam via CES1. The algorithm-based predictions were consistent with human study data. Among CES1 inhibitors and substrates identified in the literature, only dapsone and rufinamide were found to be possible in-vivo inhibitors of remimazolam metabolism. CONCLUSION: Data and analyses suggest a very low potential of remimazolam for pharmacokinetic DDIs mediated by CES1. The theoretical approach and compiled data are not specific to remimazolam and, hence, applicable in the evaluation of other CES1 substrates.

Advancements in physiologically based pharmacokinetic modeling for fedratinib: updating dose guidance in the presence of a dual inhibitor of CYP3A4 and CYP2C19.

PURPOSE: A physiologically based pharmacokinetic (PBPK) model for fedratinib was updated and revalidated to bridge a gap between the observed drug-drug interaction (DDI) of a single sub-efficacious dose in healthy participants and the potential DDI in patients with cancer at steady state. The study aimed to establish an appropriate dose for fedratinib in patients coadministered with dual CYP3A4 and CYP2C19 inhibitors, providing quantitative evidence to inform dosing guidance. METHODS: The original minimal PBPK model was developed using Simcyp® Simulator v17. The model was updated by substituting a single distribution rate (Qsac) with 2 separate rates (CLin/CLout) and transitioning to v20. Model parameter updates were further informed with 3 clinical studies, and 3 more studies served as independent validation data. The validated model was applied to simulate potential DDIs between fedratinib and a known dual inhibitor of CYP3A4 and CYP2C19 (fluconazole). RESULTS: Coadministration of fedratinib with fluconazole in patients was predicted to increase fedratinib exposure by < 2-fold in all simulated scenarios. For patients with cancer receiving the approved dose of fedratinib 400 mg once daily along with fluconazole 200 mg daily, the model predicted an approximate 50% increase in fedratinib exposure at steady state. CONCLUSIONS: The updated PBPK model improved description of the observed pharmacokinetics and predicted a low risk of clinically significant DDIs between fedratinib and fluconazole. The quantitative evidence serves as a primary foundation for providing dose guidance in clinical practice for the coadministration of fedratinib with dual CYP3A4 and CYP2C19 inhibitors.

Unexpected Sudden Deaths Following the Co-administration of Ceftriaxone and Lansoprazole: A Case Series.

Ceftriaxone and lansoprazole are commonly used in clinical settings, but recent analyses indicate a potential risk for QTc prolongation and cardiac events when used together. This case series examines three patients from a cohort of sudden death cases at a single institution over a decade, who received both medications within 24 hours before death. Three cases were identified, each with contributing factors for cardiac arrhythmias. The results underscore the importance of monitoring and possibly avoiding this drug combination in patients at risk of QT prolongation, pending further investigation into the underlying mechanisms.

Utility of Chimeric Mice with Humanized Livers for Predicting Hepatic Organic Anion - Transporting Polypeptide 1B (OATP1B) - Mediated Clinical Drug-Drug Interactions.

The influence of transporters on the pharmacokinetics of drugs is being increasingly recognized, and drug-drug interactions (DDIs) via modulation of transporters could lead to clinical adverse events. Organic anion-transporting polypeptide 1B (OATP1B) are liver specific uptake transporters in humans that can transport a broad range of substrates, including statins. It is a challenge to predict OATP1B-mediated DDIs using preclinical animal models because of species differences in substrate specificity and abundance levels of transporters. PXB-mice are chimeric mice with humanized livers that are highly repopulated with human hepatocytes and have been widely used for drug metabolism and pharmacokinetics studies in drug discovery. In the present study, we measured the exposure increases (blood AUC and Cmax) of ten OATP1B substrates in PXB-mice upon co-administration with rifampin, a potent OATP1B specific inhibitor. These data in PXB-mice were then compared with the observed DDIs between OATP1B substrates and single-dose rifampin in humans. Our findings suggest that the DDIs between OATP1B substrates and rifampin in PXB-mouse are comparable with the observed DDIs in the clinic. Since most OATP1B substrates are metabolized by CYPs and/or are substrates of P-glycoprotein (P-gp), we further validated the utility of PXB-mice to predict complex DDIs involving inhibition of OATP1B, CYPs and P-gp using CsA and gemfibrozil as perpetrators. Overall, the data support that the chimeric mice with humanized livers could be a useful tool for the prediction of hepatic OATP1B-mediated DDIs in humans. Significance Statement The ability of PXB-mouse with humanized liver to predict OATP1B-mediated drug-drug interactions (DDIs) in humans was evaluated. The plasma exposure increases of ten OATP1B substrates with rifampin, an OATP1B inhibitor, in PXB-mice have a good correlation with those observed in humans. More importantly, PXB-mice can predict complex DDIs including inhibition of OATP1B, CYPs and P-gp in humans. PXB-mice are a promising useful tool to assess OATP1B-mediated clinical DDIs.

Determination of anamorelin concentration in human plasma using a simple high-performance liquid chromatography-ultraviolet detection method.

Anamorelin, a non-peptide ghrelin analog and growth hormone secretagogue, is a novel oral drug used to treat cancer cachexia. Patients with cancer cachexia frequently use several drugs and anamorelin is a substrate of cytochrome P450 (CYP) 3A4; therefore, drug-drug interactions with CYP3A4 inhibitors and inducers pose a clinical problem. In this study, we aimed to determine the concentration of anamorelin in human plasma using a simple high-performance liquid chromatography-ultraviolet (HPLC-UV)-based method. The analysis involved extracting a 200-µL plasma sample and protein precipitation using solid-phase extraction. Anamorelin was isocratically separated using a mobile phase consisting of 0.5% potassium dihydrogen phosphate (pH 4.5) and acetonitrile (61:39, v/v) on a Capcell Pack C18 MG II column (250 mm × 4.6 mm) at a flow rate of 1.0 mL/min and monitored at a detection wavelength of 220 nm. The calibration curve was linear within a plasma concentration range of 12.5-1,500 ng/mL, with a coefficient of determination of 0.9999. The intra- and inter-day coefficients of variation were 0.37-6.71% and 2.05-4.77%, respectively. The accuracy of the assay and recovery were 85.25-112.94% and > 86.58%, respectively. This proposed HPLC-UV method is simple and can be applied in clinical settings.

Harnessing large language models' zero-shot and few-shot learning capabilities for regulatory research.

Large language models (LLMs) are sophisticated AI-driven models trained on vast sources of natural language data. They are adept at generating responses that closely mimic human conversational patterns. One of the most notable examples is OpenAI's ChatGPT, which has been extensively used across diverse sectors. Despite their flexibility, a significant challenge arises as most users must transmit their data to the servers of companies operating these models. Utilizing ChatGPT or similar models online may inadvertently expose sensitive information to the risk of data breaches. Therefore, implementing LLMs that are open source and smaller in scale within a secure local network becomes a crucial step for organizations where ensuring data privacy and protection has the highest priority, such as regulatory agencies. As a feasibility evaluation, we implemented a series of open-source LLMs within a regulatory agency's local network and assessed their performance on specific tasks involving extracting relevant clinical pharmacology information from regulatory drug labels. Our research shows that some models work well in the context of few- or zero-shot learning, achieving performance comparable, or even better than, neural network models that needed thousands of training samples. One of the models was selected to address a real-world issue of finding intrinsic factors that affect drugs' clinical exposure without any training or fine-tuning. In a dataset of over 700 000 sentences, the model showed a 78.5% accuracy rate. Our work pointed to the possibility of implementing open-source LLMs within a secure local network and using these models to perform various natural language processing tasks when large numbers of training examples are unavailable.

Dicloxacillin is an inducer of intestinal P-glycoprotein but neither dicloxacillin nor flucloxacillin increases the risk of stroke/systemic embolism in direct oral anticoagulant users.

AIM: We aimed to assess if dicloxacillin/flucloxacillin reduces the therapeutic efficacy of direct oral anticoagulants (DOACs) and the underlying molecular mechanism. METHODS: In a randomized, crossover study, we assessed whether dicloxacillin reduces oral absorption of drugs through P-glycoprotein (P-gp) during 10 and 28 days of treatment. To study the impact of dicloxacillin/flucloxacillin on intestinal and hepatic expression of P-gp in vitro, we usd LS174T cells and 3D spheroids of primary human hepatocytes. Finally, we used nationwide Danish health registries and the UK's Clinical Practice Research Datalink to estimate hazard ratios (HRs) for the risk of stroke and systemic embolism following dicloxacillin/flucloxacillin exposure among DOAC users, using phenoxymethylpenicillin and amoxicillin as active comparators. RESULTS: Dicloxacillin reduced the area under the curve of dabigatran to a geometric mean ratio 10 days of 0.67 (95% confidence interval [CI]: 0.42-1.1) and geometric mean ratio 28 days of 0.72 (95% CI: 0.39-1.4), suggesting reduced oral absorption via increased P-gp expression. In vitro, dicloxacillin raised P-gp expression in both intestinal and liver cells, while flucloxacillin only affected liver cells. In the pharmacoepidemiologic study, dicloxacillin and flucloxacillin were not associated with increased risk of stroke/systemic embolism (dicloxacillin vs. phenoxymethylpenicillin HR: 0.93, 95% CI: 0.72-1.2; flucloxacillin vs. amoxicillin HR: 0.89, 95% CI: 0.51-1.5). CONCLUSIONS: Dicloxacillin increases expression of intestinal P-gp, leading to reduced oral absorption of dabigatran. However, concomitant use of dicloxacillin/flucloxacillin was not associated with stroke and systemic embolism among DOAC users, suggesting no clinical impact from the drug-drug interaction between dicloxacillin/flucloxacillin and DOACs.

Tracing the Evolution: A Comprehensive Bibliometric Analysis of Drug Interaction Clinical Studies.

This study aims to meticulously map the bibliometric landscape of drug-drug interactions (DDIs) in clinical research. This represents the first use of bibliometric analysis to comprehensively highlight the evolutionary trends and core themes in this critical field of pharmacology. An exhaustive bibliometric search was performed within the Web of Science Core Collection, aiming to comprehensively gather literature on DDIs in clinical settings. A combination of sophisticated analytical tools including DIKW, VOSviewer, and Citespace was utilized for an in-depth exploration of bibliometric patterns and trends. Of the 3421 initially identified articles, 2622 were considered relevant. The analysis revealed a marked escalation in DDIs publications, with a peak observed in 2020. Five principal thematic clusters emerged: Safety and Adverse Reactions, Drug Metabolism and Efficacy, Disease and Drug Treatment, Research Methods and Practices, and Special Populations and Combined Medication. Key insights included the escalating significance of drug metabolism in pharmacokinetics, heightened focus on cardiovascular and antiviral therapeutics, and the advancing frontier of personalized medicine. Additionally, the analysis underscored the necessity for strategic attention to vulnerable populations and innovative methodological approaches. This study calls for the global harmonization of research methods in DDIs clinical investigations, advocating for the integration of personalized medicine paradigms and the implementation of cutting-edge computational analytics. It highlights the imperative for inclusive and collaborative research approaches to adeptly address the intricate challenges of contemporary pharmacotherapy.

Insights into pharmacogenetics, drug-gene interactions, and drug-drug-gene interactions.

This review explores genetic contributors to drug interactions, known as drug-gene and drug-drug-gene interactions (DGI and DDGI, respectively). This article is part of a mini-review issue led by the International Society for the Study of Xenobiotics (ISSX) New Investigators Group. Pharmacogenetics (PGx) is the study of the impact of genetic variation on pharmacokinetics (PK), pharmacodynamics (PD), and adverse drug reactions. Genetic variation in pharmacogenes, including drug metabolizing enzymes and drug transporters, is common and can increase the risk of adverse drug events or contribute to reduced efficacy. In this review, we summarize clinically actionable genetic variants, and touch on methodologies such as genotyping patient DNA to identify genetic variation in targeted genes, and deep mutational scanning as a high-throughput in vitro approach to study the impact of genetic variation on protein function and/or expression in vitro. We highlight the utility of physiologically based pharmacokinetic (PBPK) models to integrate genetic and chemical inhibitor and inducer data for more accurate human PK simulations. Additionally, we analyze the limitations of historical ethnic descriptors in pharmacogenomics research. Altogether, the work herein underscores the importance of identifying and understanding complex DGI and DDGIs with the intention to provide better treatment outcomes for patients. We also highlight current barriers to wide-scale implementation of PGx-guided dosing as standard or care in clinical settings.

Characterization and prediction of OATP1B activity in prostate cancer patients on abiraterone acetate using endogenous biomarker coproporphyrin I.

Organic anion transporting polypeptide (OATP) 1B1 and OATP1B3 are important hepatic transporters. We previously identified OATP1B3 being critically implicated in the disposition of abiraterone. We aimed to further investigate the effects of abiraterone on the activities of OATP1B1 and OATP1B3 utilizing a validated endogenous biomarker coproporphyrin I (CP-I). We utilized OATP1B-transfected cells to characterize the inhibitory potential of abiraterone against OATP1B-mediated uptake of CP-I. Inhibition constant (Ki) was incorporated into our physiologically based pharmacokinetic (PBPK) modeling to simulate the systemic exposures of CP-I among cancer populations receiving either our model-informed 500 mg or clinically approved 1000 mg abiraterone acetate (AA) dosage. Simulated data were compared with clinical CP-I concentrations determined among our 9 metastatic prostate cancer patients receiving 500 mg AA treatment. Abiraterone inhibited OATP1B3- but not OATP1B1-mediated uptake of CP-I in vitro, with an estimated Ki of 3.93 µM. Baseline CP-I concentrations were simulated to be 0.81 {plus minus} 0.26 ng/mL, and determined to be 0.72 {plus minus} 0.16 ng/mL among metastatic prostate cancer patients, both of which were higher than those observed for healthy subjects. PBPK simulations revealed an absence of OATP1B3-mediated interaction between abiraterone and CP-I. Our clinical observations confirmed that CP-I concentrations remained comparable to baseline levels up to 12 weeks post 500 mg AA treatment. Using CP-I as an endogenous biomarker, we identified the inhibition of abiraterone on OATP1B3 but not OATP1B1 in vitro, which was predicted and observed to be clinically insignificant. We concluded that the interaction risk between AA and substrates of OATP1Bs is low. Significance Statement We utilized the endogenous biomarker coproporphyrin I (CP-I) and identified abiraterone as a moderate inhibitor of organic anion transporting polypeptide (OATP) 1B3 in vitro. Subsequent physiologically based pharmacokinetic (PBPK) simulations and clinical observations suggested an absence of OATP1B-mediated interaction between abiraterone and CP-I among prostate cancer patients. This multi-pronged study concluded that the interaction risk between abiraterone acetate and substrates of OATP1Bs is low, demonstrating the application of PBPK-CP-I modelling in predicting OATP1B-mediated interaction implicating abiraterone.

Real-World Evidence Application in Translational Medicine: Making Use of Prescription Claims to Inform Drug-Drug Interactions of a New Psoriasis Treatment.

Patients with psoriasis often take multiple medications due to comorbidities, raising concerns about drug-drug interactions (DDIs) during the development of new medicines. DDI risk assessments of a new small molecule showed risks of CYP3A4 autoinduction and being a sensitive CYP3A4 substrate. We conducted a real-world evidence (RWE) claims analysis to assess the frequency of prescription claims for up to 12 months from the date of the initial psoriasis diagnosis for drugs that may interact with CYP3A4 substrates. We used 2013 to 2018 patient data from the US Merative MarketScan Research Database. Among patients diagnosed with psoriasis, less than 1% had a claim for a moderate/strong inducer, but up to 15% had a claim for moderate/strong inhibitor. Most prescriptions for CYP3A4 inhibitors or inducers included antibiotics and anticonvulsants. While CYP3A4 inducers were rarely used, those treated received more than >90 days treatment. Then, these RWE data were used to inform the early translational medicine strategy for the new investigational drug by strategically integrating DDI evaluations into a first-in-human healthy volunteer trial prior to studies in patients with psoriasis. The resulting DDI substudy showed that the investigational small molecule did not induce midazolam clearance but was sensitive to CYP3A inhibition, leading to the decision to exclude concomitant use of strong CYP3A4 inducers or inhibitors from clinical trials.

Cytochrome P450-mediated metabolic interactions between donepezil and tadalafil in human liver microsomes.

Donepezil and tadalafil, commonly prescribed among older persons to treat dementia and erectile dysfunction, respectively, are primarily metabolized by cytochrome P450 (CYP) 3A4. However, the drug-drug interactions (DDIs) of these drugs are unknown. Therefore, this study evaluated the CYP-mediated metabolic interaction between donepezil and tadalafil using pooled human liver microsomes (HLMs) to predict their DDI potential. Donepezil metabolism was tadalafil-concentration dependently changed in HLMs incubated with 0.1 µM donepezil and showed the maximum 32.3% increase in the donepezil half-life at 1 µM tadalafil. The formation rates of donepezil metabolites, such as N-desbenzyl donepezil and 3-hydroxy donepezil, decreased by 28.3% and 30.3%, respectively, in HLMs incubated with 1 µM tadalafil and 0.1 µM donepezil. In contrast, neither the half-life of tadalafil nor the production rate of its metabolite, desmethylene tadalafil, was changed by >20% in the presence of donepezil (up to 1 µM). CYP3A4 activity was inhibited by tadalafil with an IC50 value of 22.6 µM but not by donepezil. After pre-incubating HLMs with tadalafil and NADPH, the tadalafil IC50 value against CYP3A4 was approximately 7.04-fold lower, suggesting time-dependent tadalafil inhibition. This study shows that the DDI between donepezil and tadalafil is primarily due to time-dependent inhibition against CYP3A4 by tadalafil.

Mechanism-based inactivation of cytochromes P450: implications in drug interactions and pharmacotherapy.

Cytochrome P40 (CYP) enzymes dominate the metabolism of numerous endogenous and xenobiotic substances. While it is commonly believed that CYP-catalysed reactions result in the detoxication of foreign substances, these reactions can also yield reactive intermediates that can bind to cellular macromolecules to cause cytotoxicity or irreversibly inactivate CYPs that create them.Mechanism-based inactivation (MBI) produces either irreversible or quasi-irreversible inactivation and is commonly caused by CYP metabolic bioactivation to an electrophilic reactive intermediate. Many drugs that have been known to cause MBI in CYPs have been discovered as perpetrators in drug-drug interactions throughout the last 20-30 years.This review will highlight the key findings from the recent literature about the mechanisms of CYP enzyme inhibition, with a focus on the broad mechanistic elements of MBI for widely used drugs linked to the phenomenon. There will also be a brief discussion of the clinical or pharmacokinetic consequences of CYP inactivation with regard to drug interaction and toxicity risk.Gaining knowledge about the selective inactivation of CYPs by common therapeutic drugs helps with the assessment of factors that affect the systemic clearance of co-administered drugs and improves comprehension of anticipated interactions with other drugs or xenobiotics.

Nirmatrelvir/ritonavir: real world drug-drug interaction management experience.

BACKGROUND: In the UK, a regional vertical system for the delivery of COVID-19 medicines has been in place. This enabled centralization of expertise in risk stratification of patients, and in understanding and mitigating drug-drug interactions. RESEARCH DESIGN AND METHODS: We analyzed real-world drug-drug interactions in adult patients referred for nirmatrelvir/ritonavir therapy across one such geographic area covering 2.2 million London citizens. RESULTS: Among 208 who received NMV/r therapy, we identified 184 potential DDIs, 8% precluded nirmatrelvir/ritonavir use, 53% required management, but 56% of these did not have documented advice to hold therapy. CONCLUSIONS: This highlights the need to maintain and develop pathways for clinical pharmacology expertise in COVID-19 management.

Physiologically based pharmacokinetic modeling in obesity: applications and challenges.

INTRODUCTION: Rising global obesity rates pose a threat to people's health. Obesity causes a series of pathophysiologic changes, making the response of patients with obesity to drugs different from that of nonobese, thus affecting the treatment efficacy and even leading to adverse events. Therefore, understanding obesity's effects on pharmacokinetics is essential for the rational use of drugs in patients with obesity. AREAS COVERED: Articles related to physiologically based pharmacokinetic (PBPK) modeling in patients with obesity from inception to October 2023 were searched in PubMed, Embase, Web of Science and the Cochrane Library. This review outlines PBPK modeling applications in exploring factors influencing obesity's effects on pharmacokinetics, guiding clinical drug development and evaluating and optimizing clinical use of drugs in patients with obesity. EXPERT OPINION: Obesity-induced pathophysiologic alterations impact drug pharmacokinetics and drug-drug interactions (DDIs), altering drug exposure. However, there is a lack of universal body size indices or quantitative pharmacology models to predict the optimal for the patients with obesity. Therefore, dosage regimens for patients with obesity must consider individual physiological and biochemical information, and clinically individualize therapeutic drug monitoring for highly variable drugs to ensure effective drug dosing and avoid adverse effects.

Medicine Prescribing Practices and Prescription Errors Evaluations at Outpatient Department in Debre Berhan Comprehensive Specialized Hospital, Amhara Regional State, Ethiopia.

Background: Currently, irrational uses of medicines becoming global problem largely in developing countries like Ethiopia. Inappropriate prescribing is a major cause for poor treatment outcome and higher costs. Hence, this study was aimed to investigate medicine prescribing practice and prescription errors using WHO medicine-utilization core indicators. Methods: A hospital based retrospective cross sectional study design was used to evaluate prescribing practices and prescription errors from September to October, 2024 at the OPD pharmacy using systematic random sampling technique while a prospective approach was employed for facility indicators. Presence of potential drug-drug interactions (DDIs) were evaluated using Medscape Online Drug Interaction Checker. Data were analyzed using SPSS version 25 and interpreted as tables and figures. Results: A total of 1019 medicines were prescribed in 524 prescriptions and 81.6% (n = 832) were actually dispensed. The percentage of antibiotic, injections and medicine prescribed from Essential Drug List was 33.9% (n = 345),3.5% (n = 36) and 92.3% (n = 941) respectively. The most frequently prescribed class of medicine were antibiotics 33.9% (n = 345). 65.1% (n = 341) were ≥2 medicines and 8.3% (n = 85) had at least one potential DDIs. Among overall DDIs, the monitor closely and serious level was 60% (n = 51) and 11.8% (n = 10) respectively. The average prescription error was 4.3. Prescription errors due to failure to mention diagnosis was 40.6% (n = 213). Conclusion: Based on findings, the prescribing practices had defects to the optimum value recommended by WHO and showed high prescription errors. Antibiotics prescribing was the major problem in practice. Remarkable DDIs were observed in prescribed medicines. Therefore, designing and implementing policy to improve medicine use practice is highly indispensable.

A descriptive analysis of drug-drug interactions and corresponding adverse drug reactions in multimorbid older inpatients: findings from the SENATOR trial.

PURPOSE: Drug-drug interactions (DDIs) are prevalent among multimorbid and polymedicated older adults and can increase the risk of adverse drug reactions (ADRs), hospital admissions, and mortality. This study describes the incidence and prevalence of 66 clinically relevant DDIs and analyses the occurrence of 12 corresponding predefined ADRs in older inpatients enrolled in the SENATOR trial. METHODS: The sub-study of the SENATOR trial that involved 1537 multimorbid older inpatients, recruited from 2016 to 2018 in six academic teaching hospitals in Belgium, Iceland, Ireland, Italy, Scotland, and Spain respectively, and analysed 66 potentially clinically significant DDIs. Descriptive analysis determined DDI and corresponding ADR prevalence/incidence. RESULTS: At baseline (median age: 78 [72, 84], 52.8% male), the prevalence of patients with DDIs was high (50.9%), increased during hospitalisation (55.2%) and reduced to 49.7% after 12 weeks. The most common DDIs were: ≥ 2 potassium reducing drugs (17.1%), ≥ 3 centrally acting drugs (9.0%), and SSRI + loop/thiazide diuretic (7.2%). Of all participants, one-third experienced a prevalent (36.6%)/incident (35.8%) ADR. Major serum electrolyte disturbance had the highest incidence (10.7%)/prevalence (11.5%). Incident ADRs were more common in patients with DDIs (p = 0.013). A higher prevalence of new onset falls (p = 0.013), major constipation (p = 0.004), and major serum electrolyte disturbances (p = 0.006) was observed in patients with related and thus potentially causal DDIs. CONCLUSIONS: Clinicians should, be aware of DDIs and the involved drug classes that can lead to an increased rate of ADRs in older multimorbid inpatients. Regularly reevaluating the appropriateness of the frequently prescribed drug classes and initiating judicious deprescribing is recommended.